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275 articles for “predictive modeling”
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An Efficient and Simple Higher Order of Shear Deformation Theory for Static and Free Vibration of Laminated Composite Plates
Abstract: In the present study, the static and free vibration of laminated composite plates is examined by using a refined shear deformation theory and developed for a bending analysis of orthotropic laminated composite plates. These models take into account the parabolic distribution of transverse shear stresses and satisfy the condition of zero shear stresses on the top and bottom surfaces of the plates. The most interesting feature of this theory is …
Published in International Journal of Composite Materials and Matrices · Vol. 2, Issue 1, 2016 · pp. 23–42 Read article
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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Deep Learning Approach Based Brain Tumor Detection
Abstract: The brain tumor is one of the most deadly disease which is of great concern and hence to detect and extract the effected tumor area in the brain from the MRI has lot of research potential. It is also a very difficult task to perform by the experts. The perfection of the vivisection depends on how much experienced the radiologist or the clinical expert is. So to overcome the wastage …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 8, Issue 1, 2022 · pp. 57–63 Read article
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Cost-Constrained Sensor Reduction for Deployment AwareIoT-Based Multiclass Water Quality Monitoring
Abstract: Large-scale Internet of Things deployment for water quality monitoring systems is bounded by the capital and several other costs associated with the multi-dimensional sensor. While prior research demonstrates strong predictive performance using multi- parameter physicochemical sensing, limited attention has been given to explicit sensing cost constraints and deployment feasibility. This work formulates multiclass water quality classification as a cost-constrained learning problem in which sensing dimensionality is minimized subject to bounded …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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A Comprehensive Exploration of the Determinants Influencing Health-Related Quality of Life Among Patients Diagnosed with Coronary Artery Disease
Abstract: Background: Globally, coronary artery disease (CAD) is a major cause of illness and death. Health-related quality of life (HRQoL) is becoming increasingly acknowledged as a crucial component of patient care, even though clinical management has improved results. Objectives: To determine and assess the main factors – such as behavioural, psychological, clinical, and sociodemographic ones – that affect HRQoL in patients with CAD. Methods: Three tertiary hospitals’ worth of 300 CAD …
Published in International Journal of Cardiovascular Nursing · Vol. 11, Issue 2, 2025 · pp. 1–6 Read article
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Innovations and Sustainability in Structural Engineering:Advanced Materials, Seismic Retrofitting, andComputational Analysis
Abstract: Abstract This paper explores the latest advancements in structural engineering, emphasizing sustainable practices, the development of advanced materials, and innovative computational techniques for structural analysis. Structural engineering, a fundamental discipline within civil engineering, is experiencing significant growth due to increasing environmental challenges, stricter building codes, and the need for more resilient infrastructure. To meet modern demands, advanced materials like high-performance concrete, fiber-reinforced polymers (FRPs), and shape memory alloys (SMAs) have …
Published in International Journal of Structural Engineering and Analysis · Vol. 10, Issue 2, 2024 Read article
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Optimization of Machining Parameters for Nylon 6 Composite in CNC Lathe Using PCA-Based TOPSIS
Abstract: This work investigates the parametric optimization of CNC turning operation for Nylon 6 with principal component analysis (PCA) and technique for order preference by similarity to ideal solution (TOPSIS) based on Taguchi approach. Taguchi’s L16 orthogonal array takes 16 experimental runs to execute the design matrix of turning parameters through PCA coupled with TOPSIS, utilizing relevant experimental data as obtained through experimentation. Turning speed (TS), feed rate (FD) and depth …
Published in International Journal of Manufacturing and Materials Processing · Vol. 4, Issue 1, 2018 · pp. 36–47 Read article
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Application of Artificial Neuron Network in roughness prediction: A case study in turning of stainless steel
Abstract: - Artificial neural networks offer a practical and efficient way to choose the best machining parameters for the turning process in order to reduce surface roughness, the resulting cutting forces, and maximize tool life. Surface roughness is a significant aspect in the evaluation of cutting performance and plays a significant role in the manufacturing process. The goal of this project is to create a model based on an Artificial Neural …
Published in International Journal of Computer Aided Manufacturing · Vol. 8, Issue 1, 2022 · pp. 21–26 Read article
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Ethereum Price Prediction Using Extra Trees and Random Forest Regressors
Abstract: The Ethereum market is famous for its unpredictability and the possibility of significant profits, presenting both opportunities and obstacles for investors and stakeholders. Given the dynamic nature of this ecosystem, accurate prediction of Ethereum’s price movements is essential for informed decision-making. In this project, we propose an innovative approach that leverages ensemble learning techniques, specifically extra trees and random forest regressors, for Ethereum price prediction. By harnessing a diverse dataset …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 2, 2024 · pp. 9–25 Read article
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Optimization of Compressive Strength of Segmental Interlocking Stones
Abstract: The failure of most segmental interlocking stones used as pavement materials is traceable to lack of knowledge of the mix ratios that would optimize the compressive strength of the end products. In this study, the compressive strength was optimized based on Scheffe’s simplex lattice approach. The reliability of model developed was investigated using F-statistic and was found to be adequate. A computer program written in basic language was used to …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 4, Issue 2, 2018 · pp. 1–7 Read article
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An Efficient Machine Learning System forPrediction of Water Quality with Explainable AI
Abstract: Abstract Water availability and quality have been issues globally, especially in developing nations. Unchecked urbanization and industrialization contaminate natural water supplies and aquifers, potentially introducing physical, chemical, and biological contaminants. Over 80% of illnesses are caused by drinking tainted water, according to a WHO assessment. As clean water sources become more at risk, water quality protection has become of human, environmental, and economic importance worldwide. These water sources, crucial for …
Published in International Journal of Water Resources Engineering · Vol. 11, Issue 1, 2025 · pp. 33–42 Read article
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Data-Driven Multiscale Design of Nanostructured Composite Materials for Sustainable Engineering Applications.
Abstract: The increasing demand for high-performance, lightweight, and environmentally sustainable materials has accelerated the advancement of nanostructured composite systems in modern engineering. This study develops a comprehensive data-driven framework for the multiscale design and optimization of nanostructured composite materials, with emphasis on the interaction between structure–property relationships across nano-, micro-, and macro-scales. By integrating hybridization strategies with intelligent manufacturing techniques—such as machine learning-assisted modeling and additive fabrication—the research addresses critical limitations …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 48–58 Read article
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DESIGN AND ESTIMATION OF RESIDENTIAL BUILDING USING ETABS AND QUANTITY TAKE OFF SOFTWARE: A REVIEW
Abstract: The drafting, study, and design of a building are the most critical phases in its construction and planning. The project that will be completed is the construction of a multi-story building that will be used as a home. According to the requirements and available space, the building plan was created using AutoCAD software. The ETABS programme was used to evaluate and construct the superstructure, or the building frame. A quantity …
Published in International Journal of Architectural Heritage · Vol. 4, Issue 1, 2021 · pp. 1–3 Read article
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Prediction of Adsorption Energies using Machine Learning
Abstract: In this article, we have a much more comprehensive method that promotes the exploration of automated descriptors. Primary component analysis (PCA) with varimax rotation is used to find the strongest minimum range of adsorption energies that can be used as metal descriptors for a given data set. Our findings demonstrate that the mixture of descriptors produced by this method outperforms conventional descriptors such as nuclear carbon, hydrogen and oxygen adsorption …
Published in International Journal of Electrical Power System and Technology · Vol. 6, Issue 2, 2020 · pp. 38–46 Read article
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Predicting the Influence of Permeability’s on Settlement of Shallow Foundation
Abstract: Foundation settlement rose as soil permeability increased, excess pore pressure increased with depth, and decreased as shear modulus increased. The expanding soil cycle (shrinkage and expansion) that is principally responsible for foundation settlement is strongly related to water content. The application of modeling and simulation was used to monitor the effect of various soil properties on foundation settlement. But the focus of this study is on Permeability including other soil …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 1, 2023 · pp. 36–54 Read article
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Predictive Farming Using Image Based Machine Learning
Abstract: Agriculture sector is considered as central pillar of Indian economics contributing approximately18% of total GDP employing almost 78% of rural population. Export of agro- based commodities hasincreased by 7-folds in past 1.5 decade. Therefore, it is necessary to uplift quality of agro-commoditiesproductions. Improving crop quality and quantity by sowing appropriate crop according to soil typeand weather condition become an hour’s need today. There are variety of soil series available in …
Published in International Journal of Agrochemistry · Vol. 7, Issue 1, 2021 · pp. 24–32 Read article
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Thermodynamic Equilibrium Modeling of Sunflower Husk Gasifier to Produce Synthesis Gas
Abstract: Energy from biomass offers the great attraction in producing useful gaseous component resulting in low emissions and providing energy security. In the present study a gasifier model was developed using commercial Aspen Plus simulator. The model developed was based on the minimization of Gibb’s free energy and is validated with the experimental data of sunflower husk gasification using air as a gasifying agent. The results predicted are in good agreement …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 2, Issue 2, 2016 · pp. 14–24 Read article
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Finite Element Analysis of Composite Pressure Vessel with Non-Geodesic Fiber Trajectory In view of Friction Factors on Cylinder and End Domes
Abstract: Composites are materials created by dissimilar materials with a view to improve the properties or to create materials with desired properties. Progressive Fiber Polymer Composites have developed as an essential class of industrial materials for load carrying applications with well-rounded properties for many industrial and social applications. Structures like pressure vessels, pipes and motor casings made-up of Filament Winding technology are widely used in aerospace applications. Conventionally, pressure vessels were …
Published in International Journal of Composite Materials and Matrices · Vol. 7, Issue 2, 2021 · pp. 9–21 Read article
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Blood Group Prediction Using Fingerprint
Abstract: There is a widespread need worldwide for a cost-effective solution to measure blood groups, especially critical in underprivileged regions. Leveraging Image Processing, a prevalent technology in both affluent and resource-limited areas, presents a viable option for addressing this demand. This project advocates for the use of Image Processing algorithms and detection models to non-invasively ascertain blood groups. Its goal is to offer workable solutions for creating a point-of-care instrument that …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 9, Issue 2, 2023 · pp. 1–6 Read article